Currently submitted to: JMIR Cardio
Date Submitted: Mar 24, 2026
Open Peer Review Period: Mar 27, 2026 - May 22, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Evolving clinical perspectives on Artificial Intelligence in Interventional Cardiology: A Longitudinal Study
ABSTRACT
Background:
Artificial intelligence (AI) has demonstrated considerable potential in cardiovascular medicine, including image interpretation, risk stratification, and procedural guidance. However, translation into routine clinical practice remains limited, particularly in interventional cardiology (IC). Beyond technical performance, successful implementation depends on clinicians’ knowledge, expectations and attitudes toward AI. Over the past five years, rapid developments in both medical and non-medical AI may have influenced these factors
Objective:
To assess longitudinal changes in interventional cardiologists’ perceptions of artificial intelligence, including knowledge, expectations, attitudes and implementation barriers.
Methods:
Semi-structured interviews were conducted as a longitudinal assessment, with an initial round in 2020 and follow-up in 2025 among the same cohort of ten interventional cardiologists. An identical questionnaire was administered at both time points to assess AI knowledge, expectations, attitudes toward engagement, perceived applications and implementation barriers.
Results:
Self-rated AI knowledge increased over time, accompanied by greater confidence that AI will play a meaningful role in IC and by shorter expected timelines to clinical impact. Expectations became more heterogeneous, while willingness to learn about AI, contribute to development and use AI in clinical practice remained high. Perceived barriers shifted from trust, generalizability and cost to digital infrastructure, regulatory and legal requirements and safety issues. Perspectives on clinical applicability evolved toward more specific use cases, including lesion assessment, procedural planning and workflow optimization
Conclusions:
Despite minimal current implementation of AI in IC, interventional cardiologists demonstrate increasing familiarity with AI, greater confidence in its future role and sustained willingness to engage with AI-enabled tools, suggesting growing readiness for structured clinical adoption of AI and informing future strategies for education, governance and responsible deployment in IC.
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